There has been used an image matching technique for comparing (i) image data obtained by scanning a document with a scanner etc. and (ii) preliminarily stored image data of a reference document, so as to determine a similarity between the image data and the preliminarily stored image data.
Examples of a method for determining a similarity include: a method in which a keyword is extracted from an image with OCR (Optical Character Reader) etc. so as to carry out matching with the keyword; a method in which a target image is limited to an image with ruled lines and matching is carried out based on features of the ruled lines (see Patent Document 1); and a method in which a similarity is determined based on distribution of color components of an input image and a reference document (see Patent Document 2).
Patent Document 3 discloses a technique in which a descriptor is generated from features of an input document and matching between the input document and a document in a document database is performed using the descriptor and a descriptor database in which the descriptor is stored and which is indicative of a list of a document including features from which the descriptor is extracted. The descriptor is selected in such a manner as to be invariable to distortion caused by digitalization of a document or to a difference between the input document and a document used for matching in the document database.
In the technique, when the descriptor database is scanned, votes for individual documents in the document database are accumulated, and a document with the largest number of votes obtained or a document whose number of votes obtained is over a certain threshold value is considered as a matching document.
Furthermore, Patent Document 4 discloses a technique in which plural feature points are extracted from a digital image, a set of local feature points are determined out of the extracted feature points, a partial set of feature points is selected out of the determined set of local feature points, invariants relative to geometric transformation each as a value characterizing the selected partial set is calculated in accordance with plural combinations of feature points in the partial set, features are calculated by combining the calculated invariants, and a document or an image with the calculated features in a database is voted for, thereby searching a document or an image corresponding to the digital image.
Using such a document matching technique, conventional image data output processing apparatuses such as copying machines, facsimiles, scanners, and multi-function printers, for performing an output process such as a copy process, a transmission process, an editing process, and a filing process of input image data, are designed such that when input image data is similar to image data of a reference document, an output process of the input image data is regulated.
For example, as to a color image forming apparatus, there has been known a technique for preventing forgery of a paper currency or a valuable stock certificate. In the technique, it is determined whether input image data is image data of a paper currency, a valuable stock certificate etc. (reference document) in accordance with a pattern detected from the input image data, and when the input image data is image data of a reference document, a specific pattern is added to an output image so that an image forming apparatus having copied is specified based on the output image, a copied image is blacked out, or copy operation is prohibited.
Furthermore, Patent Document 5 discloses a technique in which image features such as color features, luminance features, texture features, and shape features and text features consisting of text codes are extracted from a process-target region including a page image in a matching target image in accordance with the number of page images in the matching target image, and a matching original image is searched in accordance with the extracted features, so that original electronic data is extracted from a paper document having been subjected to N-up printing.    Patent Document 1: Japanese Unexamined Patent Publication No. Tokukaihei 8-255236 (published on Oct. 1, 1996)    Patent Document 2: Japanese Unexamined Patent Publication No. Tokukaihei 5-110815 (published on Apr. 30, 1993)    Patent Document 3: Japanese Unexamined Patent Publication No. Tokukaihei 7-282088 (published on Oct. 27, 1995)    Patent Document 4: International Publication No. 2006/092957, pamphlet (published on Sep. 8, 2006)    Patent Document 5: Japanese Unexamined Patent Publication No. Tokukai 2005-4724 (published on Jan. 6, 2005)
However, conventional image data output processing apparatuses have a problem that when input image data is indicative of an N-up document, an image of a document under regulation on an output process included in the N-up document cannot be detected and is allowed to be subjected to the output process that is in fact to be regulated.
An N-up document is a document to which a plurality of document images are assigned. An example of the N-up document is an N in 1 document (N=2, 4, 6, 8, 9, etc.) made by assigning N document images to one document.
The conventional image data output processing apparatus determines a similarity between an image of an N-up document and a reference document while regarding the image of the N-up document as one document image. For example, even when input image data is indicative of a 2 in 1 document to which documents A and B are assigned as shown in FIG. 26(a), features of an image are calculated as one document image, and a similarity between the image of the N-up document and the reference document is determined.
Consequently, in a case where both of the documents A and B are reference documents, when the features of the 2 in 1 document largely match features of the document A and the number of votes obtained for the document A exceeds a threshold value, the 2 in 1 document is determined as only the document A and therefore no similarity is determined with respect to features of the document B.
As a result, when the document A is under a mild regulation such as outputting with reduced resolution, the document B is processed together with the document A even when the document B is prohibited from being output. This leads to outflow of information of the document B.
In the above example, an explanation was made as to a case where the number of votes obtained for the document A in the 2 in 1 document is larger than the threshold value. However, there could be a case where both of the numbers of votes obtained for the documents A and B respectively in the 2 in 1 document are not more than the threshold value and consequently it is determined that both of the documents A and B are not reference documents. In this case, the documents A and B are output without any regulation.
In contrast thereto, there is a case where both of the numbers of votes obtained for the documents A and B respectively exceed the threshold value as shown in FIG. 27. In this case, there would be no problem if the input image data would be determined as being similar to both the documents A and B. However, it is never determined that the input image data is similar to a 2 in 1 document including the documents A and B. Consequently, when the input image data is determined as similar to the document A with the highest number of votes obtained, no regulation is made as to output of the document B. That is, similarly with the above, in the case where the input image data is indicative of a 2 in 1 document in which the documents A and B are assigned, when it is determined that the input image data is similar to the document A that is allowed to be output, the document B is output together with the document A even if the document B is in fact not allowed to be output.
The N-up document includes document images that are downsized from their original sizes. There is a case where features calculated from a downsized image are different from features of a reference document that is not downsized. In this case, accuracy in similarity determination drops.
To be more specific, in a method for calculating features based on feature points, there is a case where the downsized N-up document and the reference document that is not downsized have different connected components from which feature points are calculated. For example, partial images that have a certain distance therebetween in the reference document are determined as different connected components, whereas the partial images are connected with each other in a downsized N in 1 document and therefore determined as one connected component.
As described above, when connected components from which features are calculated are different between an N-up document and a reference document, different features are calculated between the N-up document and the reference document. This may cause a determination that the N-up document is not the reference document.
Patent Document 5 describes that a matching original image is searched by extracting image features and text features from an assigned image region that is a process-target region. This arrangement necessitates a user to input the number of images laid out on the N-up document or requires determination for determining whether a matching target image is an N-up document or not. In the former case, a notion of the number of documents in an N-up document is not generally known to a user and therefore it is necessary to explain to the user what is “the number of documents in an N-up document” and to receive an input of the number, which drops efficiency in the process. In the latter case, it is necessary to separately provide an arrangement for determining whether a matching original image is an N-up document or not.
Further, since text codes subjected to an OCR process are used as text features, it is necessary to store texts in a dictionary beforehand. This lengthens a time for similarity determination.